Generally, a manufacturing process for thin film devices of semiconductors, liquid crystal displays, hard disk magnetic heads and the like is made up of plural process steps.
The number of steps in such manufacturing process may count, in some cases, as large as hundreds. Therefore, upon occurrence of pattern abnormalities such as particle mixing or line disconnections on thin film devices due to insufficiencies or abnormalities of manufacturing conditions of the processing equipment, the probability of occurrence of product failures would increase, leading to decreases in the yield.
Accordingly, it is important to specifically determine a device unit where the problem has occurred and to take countermeasures therefor in order that the yield is maintained and improved. For this purpose, particle inspections, pattern inspections or other inspections are executed for individual main steps, respectively, thus providing supervision as to whether or not the processing goes on normally. In this case, since it is impossible to execute such inspections on all of object boards, which are those to be processed, in each processing step because of constraints in time and labor, the inspections are executed ordinarily on object boards sampled on a lot basis or object board basis or their combination basis for each sequence of several steps. It is noted that the term, object boards, herein refers to a minimum unit of object boards to be processed as products, e.g., one wafer in case of semiconductor.
With an inspection device for inspecting object wafers, in the case of particle inspections, information as to position and count of foreign particles is acquired by, for example, scanning the wafer surface with a laser to detect the presence of scattered light. Also, in execution of a defect inspection for detecting both foreign particles and pattern abnormalities, information as to position, count and the like of defects are acquired by, for example, capturing an image of a circuit pattern of the wafer with an optical scale-up image capturing device and then comparing the image with another image of a proximate identical-pattern area.
Herein, the term ‘defect’ refers to a spot where an abnormality has been found by an inspection with an inspection device.
Generally, decisions as to an abnormality of a device that has shown any of the above-described problems are made based on management indices given by the count or density of defects detected by the inspection device. That is, if the count or density of defects is larger than a previously set reference value, it is decided that an abnormality has occurred to the device, where an image of the defect is captured with a scale-up by a review device such as an optical microscope or a scanning electron microscope (hereinafter, referred to as SEM) based on defect coordinate information detected by the inspection device to acquire detailed information as to the size, shape, texture or the like of the defect, or where detailed inspections for elementary analysis, cross-sectional observation and the like are performed to specifically determine a device to which a failure has occurred or the content of the failure. Then, based on results of such procedure, countermeasures on the device or process are taken so as to prevent declines in the yield.
In order to achieve automatization and higher efficiency of such defect analyzing work, in recent years, there has been developed a review device having a function of automatically acquiring elementary analysis data of foreign particles and defects based on inspection data derived from a particle inspection device or pattern inspection device.
In addition, a method for automatically and efficiently performing composition analysis of defects is disclosed in, for example, PTL 1. Besides, methods for automatically performing EDS (Energy Dispersive X-ray Spectrometer) are disclosed in, for example, PTLs 2, 3, 4 etc.